As businesses ramp up their use of artificial intelligence (AI), marketing and CX leaders must ensure their teams are building unbiased, equitable, and ethically responsible AI systems that don’t unwittingly cross over any regulatory lines or, perhaps worse, turn customers off.
Principle #1: Fairness and bias prevention
Forrester research shows that people will walk away from a brand if they learn its AI system is making biased decisions or discriminating against anyone, Purcell said.
It’s not that Purcell thinks companies are deliberately building AI systems with bias. So how does a machine learning algorithm become biased in the first place?
Principle #2: Trust and transparency
Many AI projects fail because the AI was created as a black box, and the business stakeholder who’s going to use the system doesn’t trust it, Purcell said. “Using interpretable or explainable AI is a way of evoking trust,” he said.
Principle #3: Accountability
According to Forrester research, only 20 percent of companies said they are building their own AI systems from scratch. Meanwhile, 51 percent said they are building their systems using third-party components – “like a bunch of Lego blocks,” Purcell said – and 48 percent are buying commercially available packaged solutions with AI embedded in them.
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